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Sperling, K.* ; Scherb, H. ; Neitzel, H.*

Population monitoring of trisomy 21: Problems and approaches.

Mol. Cytogenet. 16:6 (2023)
Publ. Version/Full Text DOI PMC
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Trisomy 21 (Down syndrome) is the most common autosomal aneuploidy among newborns. About 90% result from meiotic nondisjunction during oogenesis, which occurs around conception, when also the most profound epigenetic modifications take place. Thus, maternal meiosis is an error prone process with an extreme sensitivity to endogenous factors, as exemplified by maternal age. This contrasts with the missing acceptance of causal exogenous factors. The proof of an environmental agent is a great challenge, both with respect to ascertainment bias, determination of time and dosage of exposure, as well as registration of the relevant individual health data affecting the birth prevalence. Based on a few exemplary epidemiological studies the feasibility of trisomy 21 monitoring is illustrated. In the nearer future the methodical premises will be clearly improved, both due to the establishment of electronic health registers and to the introduction of non-invasive prenatal tests. Down syndrome is a sentinel phenotype, presumably also with regard to other congenital anomalies. Thus, monitoring of trisomy 21 offers new chances for risk avoidance and preventive measures, but also for basic research concerning identification of relevant genomic variants involved in chromosomal nondisjunction.
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Publication type Article: Journal article
Document type Review
Corresponding Author
Keywords Aneuploidy ; Down Syndrome ; Epidemiology ; Preventive Medicine ; Risk Factors ; Sentinel Phenotype ; Trisomy 21; Down-syndrome; Congenital-anomalies; Human Embryos; Risk-factors; Health; Europe; Nondisjunction; Genomics; Germany; Waste
ISSN (print) / ISBN 1755-8166
e-ISSN 1755-8166
Journal Molecular Cytogenetics
Quellenangaben Volume: 16, Issue: 1, Pages: , Article Number: 6 Supplement: ,
Publisher BMC
Publishing Place Campus, 4 Crinan St, London N1 9xw, England
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)